Demonstration of a cloud-based precision farming management system for a sustainable and intensive agriculture to secure long-term food supply in Europe

Projektinformationen

AgriCloud

ID Finanzhilfevereinbarung: 672655

DOI

10.3030/672655

Projekt abgeschlossen

EK-Unterschriftsdatum 27 April 2015

Startdatum 1 Mai 2015

Enddatum 30 September 2015

Finanziert unter

• SOCIETAL CHALLENGES - Food security, sustainable agriculture and forestry, marine, maritime and inland water research, and the bioeconomy

Gesamtkosten

€ 71 429,00

EU-Beitrag

€ 50 000,00

Koordiniert durch

AGRI CON GMBH PRECISION FARMING COMPANY
Germany

Periodic Reporting for period 1 - AgriCloud (Demonstration of a cloud-based precision farming management system for a sustainable and intensive agriculture to secure long-term food supply in Europe)

Berichtszeitraum: 2015-05-01 bis 2015-09-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

European farmers are in need of yield production increasing and climate change adapting plant growth strategies to optimally supply plants achieving highest food quality and stabilizing plant growth. This can be enabled through a holistic farming management approach for variable rate applications, also known as Precision Farming (PF). Despite the progress achieved so far with a 10% market share of agronomic PF tools, a continuous growth is being hampered by the vast mass of data to evaluate and interpret by farmers, generated by different and not compatible sources. Moreover, farmers hesitated to invest in PF tools due to high investment costs, unclear economic benefits as well as higher efforts in farm management. Farmers are looking for an easy handling, time-saving and cost-efficient integral solution. So there is an excellent business opportunity for agricon to provide with AgriCloud an integrated, compatible and automatically working PF management system to boost food production in a resource-efficient and sustainable way.
The objectives were to prepare the AgriCloud market introduction thoroughly by identifying special concerns, risks, and IP issues and transforming this knowledge into a reliable and sustainable business approach. The project-specific objectives were:
• To realise customer surveys to analyse their special concerns and constraints w.r.t. PF and identify pilot customers for the first trials in target countries (Germany, Poland, Baltic States)
• To elaborate the business plan with more concrete market figures in the target countries and develop different commercialisation scenarios
• To set up a risk management plan and IP strategy
• To collect and present trusted data about PF benefits depending on farm size and crop type to increase market acceptance

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

The feasibility study comprised the following activities to economically and technically validate the project: identification of market barriers for Precision Farming (PF), prioritisation of European target markets, identification of pilot customers willing to test AgriCloud, in-depth FTO analysis, implementation of IPR management, development of calculation tool to enable farmers to calculate the economic benefit of AgriCloud for their farm and sharpening of the business plan.
The SME Instrument Phase 1 of the project has been successfully finished after five months by the end of October 2015. The results are very encouraging and enable to move the technology towards a TRL 7.
All six tasks have been executed according to the Grant Agreement. The customer survey conducted proved to be highly valuable with regard to identifying current factors which can have a positive or negative impact on the adoption of PF technology by European farmers. The market evaluation for the eight target markets identified Germany, Poland and Romania as national markets to focus on first. Seven pilot customers were identified. An extensive FTO analysis was performed and yielded full freedom-to-operate for AgriCloud. In addition, agricon has implemented in-house IPR management. A calculation tool to prove the economic benefits of AgriCloud to potential farmer customers was successfully developed and tested. The business plan has been sharpened and the technical and economic feasibility proven.
For financing, agricon will apply for SME instrument Phase 2 funding.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

As a final outcome of this project, agricon will be well positioned to implement its vision delivering smart solutions for integrated farming. In line with this vision, the business development strategy is dedicated to a change in the product portfolio composition. Today, agricon is selling sensors, software packages for area-specific crop farming, and AgriPort software licences separately. In the future, agricon wants to establish AgriCloud as the major product (SaaS), and selling the sensors and other services implemental to the core system. This business innovation project funded through the SME instrument programme in Phase 1 has already proven highly valuable in supporting that transition towards becoming a smart solution provider for integrated farming.
In the broader context, the outcome of this business innovation project demonstrates the high potential of PF technology for improving the Europe’s competitiveness in the field of agricultural high technologies. Ultimately, the success of PF technology such as AgriCloud will help to improve and reduce the ecological footprint of the European agricultural industry. At the same time, the future success of PF technologies (as it can be expected for AgriCloud) clearly will help to safeguard the economic viability of European farmers by improving the cost-efficient use of fertilisers and by providing holistic farming management tools which enable optimal yields.

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